Hepatocellular carcinoma patients with high circulating cytotoxic T cells and intra-tumoral immune signature benefit from pembrolizumab: results from a single-arm phase 2 trial

Abstract

Background: A limited number of studies have characterized genomic properties of hepatocellular carcinoma (HCC) patients in response to anti-PD-1 immunotherapy.

Methods: Herein, we performed comprehensive molecular characterization of immediate (D-42 to D-1) pre-treatment tumor biopsy specimens from 60 patients with sorafenib-failed HCC in a single-arm prospective phase II trial of pembrolizumab. Objective response rate was the primary efficacy endpoint. We used whole-exome sequencing, RNA sequencing, and correlative analysis. In addition, we performed single-cell RNA sequencing using peripheral blood mononuclear cells.

Results: The overall response rate of pembrolizumab in sorafenib-failed HCC patients was 10% ([6/60] 95% CI, 2.4-17.6). In a univariate analysis using clinicopathological features, female gender, PD-L1 positivity, and low neutrophil-to-lymphocyte ratio (NLR) were identified as contributing factors to pembrolizumab response. Somatic mutations in CTNNB1 and genomic amplifications in MET were found only in non-responders. Transcriptional profiles through RNA sequencing identified that pembrolizumab responders demonstrated T cell receptor (TCR) signaling activation with expressions of MHC genes, indicating increased levels of T cell cytotoxicity. In single-cell sequencing from 10 pre- and post-treatment peripheral blood mononuclear cells (PBMCs), patients who achieved a partial response or stable disease exhibited immunological shifts toward cytotoxic CD8+ T cells. Conversely, patients with progressive disease showed an increased number of both CD14+ and CD16+ monocytes and activation of neutrophil-associated pathways.

Conclusions: Taken together, HCC patients with infiltration of cytotoxic T cells, along with increased active circulating CD8+ T cells during pembrolizumab treatment and down-regulation of neutrophil-associated markers, significantly benefited from pembrolizumab treatment.

Trial registration: NCT#03163992 (first posted: May 23, 2017).

Keywords: Biomarkers; Carcinoma; Hepatocellular; Pembrolizumab; Tumor.

Fig. 1

Clinicopathological features in association with response to pembrolizumab. S represents each patient’s identification number. A Swimmer plot for enrolled patients (n = 60). Each lane represents a single patient’s data. B Waterfall plot of response to pembrolizumab. The Y-axis represents the percentage of maximum tumor reduction assessed according to RECIST 1.1 criteria. The lower dotted line represents tumor reduction of 30% per RECIST, which defines PR (responder). Patients with bars in blue (PD) and yellow (SD) were determined to be non-responders. C Univariate analysis to identify clinicopathological features associated with response to pembrolizumab. Odds ratio and p value for each feature were computed via Fisher’s exact test. The size of the circle represents the number of samples. D–F Tumor reduction after pembrolizumab treatment in three responders who have available PD-L1 status by immunohistochemistry (IHC) (upper panel). H&E staining and PD-L1 positivity for the three responders (lower panel). PR, partial response; SD, stable disease; PD, progressive disease; CPS, combined positive score, AFP, alpha-fetoprotein; NLR, neutrophil-to-lymphocyte ratio

Fig. 2

The genomic landscape and clinicopathological features. S represents each patient’s identification number. A Top panel shows the number of somatic mutations of each sample, mutation signature (COSMIC version 2), BOR, etiology, the scores of PD-L1 CPS, AFP, and NLR. The middle panel shows the mutational landscape of non-synonymous mutation for frequently altered genes in HCC. Green, red, purple, blue, brown, orange, and gray tiles indicate missense, nonsense, frameshift-insertion, frameshift-deletion, inframe deletion, splice site mutation, and wild-type. The bottom panel displayed copy number alteration for frequently amplified/deleted genes in HCC. Tiles in red, salmon, sky blue, and blue indicate amplification (copy number (CN) ≥ 4), gain (CN ≥ 2.5), loss (CN ≤ 1.5), and deletion (CN ≤ 1), respectively. B GSEA plot representing CHIANG_LIVER_CANCER_SUBCLASS_PROLIFERATION_UP pathway was significantly enriched in responders (PR) (FDR = 0 and normalized enrichment score (NES) = 2.53). C GSEA plot representing CHIANG_LIVER_CANCER_SUBCLASS_CTNNB1_UP pathway was significantly enriched in non-responders (SD/PD) (FDR = 0 and NES = −2.76). D ssGSEA scores of Reactome MET receptor activation geneset were significantly higher in non-responders (SD/PD) than responders (PR) (Wilcoxon rank-sum p-value = 0.016). ssGSEA scores were calculated using GSVA package in R. BOR, best overall response; CPS, combined positive score; AFP, alpha-fetoprotein; NLR, neutrophil-to-lymphocyte ratio; PR, partial response; SD, stable disease; PD, progressive disease

Fig. 3

Gene expression profiles in association with response to pembrolizumab. A A volcano plot showing the differentially expressed genes (DEGs) between responders and non-responders. Red and green dots indicate the up-regulated genes in responders (adjusted p-value < 0.05 and log2 fold change > 1) and the up-regulated genes in non-responders (adjusted p-value < 0.05 and log2 fold change < − 1). The X-axis represents the log2-fold changes in expression levels, and the Y-axis represents the statistical significances (-log10-adjusted p-value) between responders and non-responders. Each dot represents one gene. B, C A barplot illustrating the top 20 significantly overlapped MSigDB gene sets (FDR < 0.05) with the DEGs generated in A. Hypoxia was associated with up-regulated genes in responders (B), and liver/HCC-associated genesets were overlapped with up-regulated genes in non-responders (C). Red bar represents statistical significances (-log10 scale) and black dot indicates the proportion of overlapped genes in genesets. D, E GSEA plots representing PID_CD8_TCR_DOWNSTREAM pathway (FDR = 0.0028, NES = 1.81) (D) and KEGG_T_CELL_RECEPTOR_SIGNALING pathway (FDR = 0.012, NES = 1.69) (E) were significantly enriched in responders (PR). F ssGSEA scores of gene markers for neutrophil were up-regulated in non-responders (SD/PD) (Wilcoxon rank-sum p value = 0.093). DEG, differentially expressed gene; FDR, false discovery rate; GSEA, geneset enrichment analysis; NES, normalized enrichment score; PR, partial response; SD, stable disease; PD, progressive disease

Fig. 4

Single-cell characterization of immune cells via scRNA-seq. A t-stochastic neighbor embedding (tSNE) analysis of 26,541 immune cells from 10 patients before and after 2 cycles of pembrolizumab treatment. Cell type clusters were identified and annotated using scCATCH and are denoted by distinct color based on respective cell types. B tSNE analysis of immune cells colored by representative cell type markers, including S100AB, KLRF1, CD8A, and TCL1A. C Dot plot analysis of each cell type cluster and their representative markers. Colors indicate average expression levels, while the size of each dot represents the percentage of cells expressing the respective marker. D tSNE analysis of immune cells colored by patient identity. E Bar graph representation of immune cell composition based on individual patient. Each immune cell type has been normalized based on individual patient

Fig. 5

Immunological changes of immune cells in response to pembrolizumab. A tSNE analysis of immune cells colored by inferred cell type and separated by pembrolizumab treatment time point. Pre-treatment (left panel) and post-treatment (right panel). B Bar graph representation of immune cell composition based on pembrolizumab treatment time point. The p-value has been calculated using the chi-squared test. C Bar graph representation of immune cell composition based on pembrolizumab treatment time point and response. The p-values have been calculated using chi-squared tests. D Violin plot representation of cytotoxic T cells between pre- and post-pembrolizumab treatment in patients who achieve PR or SD (left panel) and patients with PD (right panel). The p values are calculated by a two-sided Wilcoxon rank-sum test. E Volcano plot representation of differentially expressed gene analysis in cytotoxic T cells between patients who achieve PR or SD and patients with PD. Genes with > 0.5 or < − 0.5 log₂ fold change and < 0.05 p-value are colored in red and blue, respectively. F Gene Ontology (GO) analysis of differentially expressed genes in E. tSNE, t-stochastic neighbor embedding; PR, partial response; SD, stable disease; PD, progressive disease